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imdb-distilbert
mowghli/imdb-distilbert
imdb-distilbert is a text classification model from mowghli. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Oct 3, 2025
- Updated
- Oct 3, 2025
- SHA
- 5f918a22
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
imdb-distilbert
This model is a fine-tuned version of mowghli/distilroberta-base-finetuned-wikitext2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7517
- Accuracy: 0.9217
- F1: 0.9207
- Precision: 0.9330
- Recall: 0.9087
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0846 | 1.0 | 1407 | 0.5710 | 0.9064 | 0.9073 | 0.9037 | 0.9109 |
| 0.0487 | 2.0 | 2814 | 0.7084 | 0.9104 | 0.9097 | 0.9223 | 0.8974 |
| 0.0627 | 3.0 | 4221 | 0.6852 | 0.9156 | 0.9163 | 0.9138 | 0.9189 |
Framework versions
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Oct 3, 2025
- Updated
- Oct 3, 2025